AI & IoT are ready to reshape assisted living
Demographics, public policy, and the labor market are driving an emerging market for IoT to deliver elder care services. By 2029, 20 percent of the U.S. population will be over the age of 65 and 70 percent of those individuals will need some form of assisted care, according to recent research. Prolonged aging is associated with cognitive decline, loss of hearing and vision, as well as other constraints on physical activity.
There are multiple ways to address this growing population. Some of this demand will be met by 29,700 senior living facilities expected by 2025 but pressures on traditional assisted living facilities are growing.
More seniors plan to live in their own homes rather than moved to a facility. Medicare and Medicaid reimbursements are not increasing and may decrease, potentially limiting the supply of traditional assisted living services.
In addition, elder care facilities have to recruit and retain knowledgeable talent in a competitive market. Artificial intelligence (AI) and the Internet of Things (IoT) have the potential to shape a new collection of technologies to improve the quality and availability of elder care while helping to control its costs.
Ambient intelligence, which combines AI and IoT, will provide real-time monitoring of an environment and event-driven response to changes in that environment. Sensors designed to detect changes in sound, motion, physiological signals, as well as more generalized image processing are core components of an ambient intelligent environment.
This type of IoT application is defined by five characteristics:
- It uses real-time context awareness,
- It is personalized to individual patients,
- It can adapt the individual characteristics and behaviors of the patient,
- It is available throughout the target environment, and
- It is transparent to the patient in that it requires no direct interaction on the part of the patient to perform its functions.
Ambient intelligence thus is poised to serve a range of functions with regards to elder care, but most applications will address three broad functional needs: maintaining routine activities and social connectedness, enhancing safety, and monitoring health.
Routine activities and social support are especially suited for elders suffering cognitive decline. These systems detect changes in patients location or environment and provide verbal assistance as needed, or if needed, notify caregivers.
Safety-enhancing sensors are often wearable and provide early warnings of potentially harmful situations, such as falls. Health monitoring systems may combine wearable and stationary sensors to monitor blood pressure, pulse, and movement of the patient as well as environmental data, such as ambient temperature.
Developers of ambient intelligence systems face challenges common to IoT as well as some specific to this domain. Real-time processing, quality control, and data integration are especially important when making decisions about the physical well being of a patient.
Unlike IoT applications that function primarily to monitor and control devices or environmental conditions, ambient intelligence systems are designed to monitor and support humans, creating an additional dimension of complexity.
IoT developers working in this space have to consider elder engagement, which is a crucial aspect of this type of system design. Research has found that the subjective experience of the patient must be taken into account when designing such systems to mitigate the risk of not adopting or subverting these systems.
For example, some elders may perceive sensors embedded in living environments as encroachments on privacy while others may feel that this type of monitoring limits their autonomy. The message from researchers is clear: designers must take into account the fact that elders are not objects to be monitored but agents who think, feel, and act in different ways under different circumstances.
ElliQ by Intuition Robotics is an example of an ambient intelligence that is designed to support, not simply monitor, independent and autonomous elders. This device makes personalized recommendations for activities and allows users to interact with through both voice and gesture. It also has an optional feature that allows family members to check in on ElliQ users.
IoT and AI are enabling ambient intelligence that can help meet the growing demand for elder care but designers must take into account the subjective and psychological factors that will strongly influence adoption of this technology.
Fortunately, designers have a number of assessment instruments to help understand what to consider when designing IoT for elder care. The Patient Activation Measure is known for its utility with patients understanding disease treatment. The Altarum Consumer Engagement (ACE) Measure™ can help measure the degree to which a patient is involved with their healthcare decision making. The Patient Enablement Instrument assess how well a patient understands condition.
These and related instruments can help healthcare practitioners tailor ambient intelligence systems for the specific needs of individual patients. They also help to highlight the psychological factors that can influence how well an ambient intelligence system is adopted by elders.